Institute of Food and Agricultural Sciences (IFAS)
Department of Animal Sciences
Quarterly Newsletter Vol. 9 No. 1 Winter 2009
New Year's Resolutions IV
David R. Bray
Happy New Year to you all! It's time again to plan for a
successful new year on your dairy, which means we
should repeat the successful things we did last year and
not repeat last year's screw-ups. This time of year is a
good time for planning, not only for this year but the
future as well; this means how do we continue to
improve the things we do well and how do we change
or eliminate those things we don't do well.
1- Know your cost of production. Dr. De Vries has a
"Cost of Production Calculator" spreadsheet.
Contact him or Dr. Ely in Georgia, or your County
Extension Agent to get it. They are happy to help.
2- Set goals for all the enterprises or areas of your
dairy. These should have employee input also
because this is the road map for success. These
goals will then set the goals for your employees to
strive to make the whole dairy's performance
better. Include safety goals.
3- These performance goals then are translated to
employee job descriptions and compensation for
their part of meeting the dairy's goals; these are
explained at the employee performance review.
4- Implement some sort of employee training program
to insure they understand their responsibilities in
this quest for excellence.
5- Do only what you can do well. If you can't raise
calves, use a calf raiser or buy replacements. If you
can't grow crops, buy them or have them custom
grown and or harvested.
6- Go visit other dairies in the Southeast. You see
these people at meetings; see what other people
are doing. Some of the most innovative dairymen in
the world live here. Go elsewhere in the country
and see what's new there; this can help in the
future planning process.
7- Replace out-dated worn out milking equipment. It's
hard to preach great milking practices when nothing
works half of the time.
8- Milk clean dry udders and post dip.
9- Keep cows as clean, cool and comfortable as
10- Inventory your blind quarters, replace missing leg
bands, apply new bands to new found blind
quarters, and cull those 2 quartered beauties.
11- Hire help with more teeth than tattoos.
12- If you get out of breath tying your shoes, lose
weight or wear boots.
13- Keep a smile on your face, people will wonder what
you are up to.
Contact Dave Bray at email@example.com or call (352) 392-
Producing Penalty Free Milk
David R. Bray
With the changing economy, what our consumers
(which include processors as well as the housewives)
want is a high quality product with a long shelf life.
Most of you are producing milk that meets these
standards now and this will have little effect on you.
Those of you that are not meetings these standards
now need to begin to strive to meet these elementary
goals before any penalties begin. The goals listed here
should be reached in the next couple years.
What do I have to do to produce penalty free milk?
Nothing more than you should have been doing now.
Components of Penalty Free Milk:
Somatic Cell Count
1. This time of year it should be 300,000 or below in
the Southeast United States.
2. To obtain low SCC post teat dip with a cup, dry treat
all cows going dry.
3. Milk clean dry udders.
4. Keep milking equipment in good working order.
5. Cull chronic cows.
6. Find all blind quarters, marking them in your
records. Band new ones and reapply bands to lost
ones. This can lower SCC by 100,000 in some herds.
7. Keep cows in a cool clean place.
8. Cull junk Cows.
9. Don't make more junk cows.
Standard Plate Count (bacteria count)
1. Adequate hot water for cleaning 1600 in vat at start
of washing dump at 1200.
2. Proper concentration of chemicals less expensive
chemicals use more product than more expensive
and more concentrated products. Your dealer
should give you a minimum amount of chemicals to
3. Replace liners at 1200 cow milking or as directions
4. Replace all rubber components every 6 months;
clean vacuum and pipe lines at this time also.
5. Adjust air injectors.
6. Milk clean dry udders.
7. Chronic high SPC: disassemble the plate cooler,
clean and replace gaskets.
8. Proper milk cooling temperature and times -
prevent freezing and make sure milk is agitated
properly. The faster the cooling the less bacteria
9. Keep cooling coils clean.
10. Cull the rest of the junk cows.
Other Quality Tests
There are other tests that are done to your milk but if
you just take care of your cows and equipment you
don't have to worry about what they test.
If you do not wish to produce high quality milk,
someone else will be happy to do it for you especially at
$2.50/gallon diesel. Contact Dave Bray at
firstname.lastname@example.org or call (352) 392-5594.
Feeding Fats to Improve Immunity and Fertility of
L. Badinga, C. Caldari-Torres, C. Risco, and C.R. Staples
Modern dairy cows experience varying degrees of
immunological dysfunction from approximately 3 weeks
before calving to 3 weeks after calving, which may have
practical implications for health and reproductive
management. Inadequate nutrition
during the transition to lactation will
affect the amount of milk produced
per cow per day of herd life, breeding
costs, rates of voluntary and
"s92u1,a involuntary culling, and the rate of
genetic progress for traits of economic
importance. Dairy simulation studies predict that a 1-
day increase in the average calving interval would cause
a net revenue loss of over $27 million to the US dairy
One of the factors contributing to low breeding
efficiency in high producing cows is the high energy
deficit of early lactation, which delays return to estrus
and impairs reproductive performance after calving.
With the support of the Florida Milk Check-Off and
Technologies, Inc., we
conducted a feeding trial
to examine the effect of
feeding calcium salts of
trans fatty acids (TFA) or
omega-6 fatty acids (n-
6FA) on immunity and
reproductive efficiency of
lactating Holstein cows.
Preliminary analyses with
a limited number of cows
indicate that dietary
trans and omega 6 fatty
acids decrease the
incidence of uterine
infections (figure 1) and
tend to improve fertility
responses in early
postpartum dairy cows
(figure 2). If repeated on
results of this research
could save millions of
dollars to the US dairy
industry by reducing
bacterial infections after
calving and decreasing
RBF TFA N-6 FA
Figu 1 Incidence of puerperalmetrltlsandsubcllnlcalendometrntli
in eary lactation dairy cows fed saturated fat (RBF), TFA or n-6 FA
RBF TFA N-6 FA
Figure 2. Conception rates to first service and days open of lactating
dairy cows fed saturated (RBF), trans (TFA) or n-6 (n-6 FA) fatty
the interval from calving to conception.
Badinga, Caldari-Torres, and Staples are in the
UF/IFAS Department of Animal Sciences. Risco is in the
College of Veterinary Medicine. Contact Lokinga
Badinga at email@example.com, or call (352) 392-1958.
Effect of Rust Infestation on Silage Quality
A.T. Adesogan, O.C.M. Queiroz, and S.C. Kim
Southern rust is an aggressive disease caused by
Puccinia polysora fungi that can destroy a corn field in a
few days. It is dispersed by airborne spores that form
orange, circular pustules mainly on the upper leaf
surface. The fungus diverts nutrients away from the
plant causing leaf death. Few corn hybrids are resistant
to southern rust and some of such varieties lack the
combination of agronomic and nutritional traits
desirable for silage production. Certain fungicides can
control the disease, but their effectiveness is limited
when applied late in the season, particularly under hot,
humid conditions (Raid and Kucharek, 2005). In addition
to causing crop losses, this disease can predispose the
plant to mold growth and mycotoxin infestation. Little
is known about the effect of the disease on the
nutritional value of corn silage. Less is known about
whether microbial inoculants that inhibit the growth of
spoilage-causing yeasts and molds can improve the
quality of rust-infested corn silage.
This project aimed to determine the effect of the
level of southern rust infestation of a corn hybrid on
silage fermentation, nutritive value and bunk life, and to
determine how inoculant application affects these
measures of forage quality. A corn hybrid (Pioneer
33V16) grown on a 130-acre field on July 6, 2007 at the
Dairy Unit was infested by southern rust after taselling.
Aerial application of a fungicide resulted in areas with
different levels of infestation in the field.
Representative samples (220 Ib each) were taken from
areas classified as having no rust (clean), medium rust
(all leaves in the bottom half of the plant were
infested), and high rust (all leaves were infested). Each
of these was ensiled without treatment (Control) or
after applying Buchneri 500 inoculant (Lallemand
Animal Nutrition, Milwaukee, WI) at a rate that supplied
4.99 x 1010 colony forming units of Pediococcus
pentosaceaus and Lactobacillus buchneri in each gram
of forage. Each treatment was ensiled in four replicate
5-gallon mini silos for 97 days.
Concentrations of dry matter (DM) and fiber
fractions increased with the level of rust infestation,
whereas DM digestibility decreased by up to 13%. These
results indicate that the rust dried the silages and
reduced their nutritive value. The DM concentration of
the high-rust corn silage (58%) was high enough to
reduce the effectiveness of packing in a farm-scale silo.
High rust silages also had lower neutral detergent fiber
digestibility (NDF) than medium rust or clean silages.
This effect was greater in inoculated silages because
inoculation increased the NDF digestibility of clean and
medium-rust silages. Silage pH increased with rust
infestation, however, all pH values were below 4.
Concentrations of lactate, total volatile fatty acids, and
most individual volatile fatty acids decreased with
increasing rust infestation in control silages, but such
trends were largely absent in inoculated silages. This
shows that rust infestation reduced the fermentation
but inoculant application reduced this negative effect.
Only, high-rust silages contained butyric acid, which is
an indicator of undesirable clostridial secondary
fermentation. Mold counts of clean and medium-rust
silages were relatively high, but high-rust silages had
fewer molds, perhaps because they were drier. Aerobic
stability was greater in high-rust silages than silages
with less rust infestation.
Inoculant treatment reduced mold counts in high
rust silages 80-fold and increased their aerobic stability
by about 75%. Aflatoxin was only detected in
uninoculated, high-rust silages and the levels exceeded
the FDA action level (20 ppb), indicating that this silage
should not be fed due to the risk of aflatoxin
transmission to milk. Surprisingly, zearalenone was only
detected in silages with no rust infestation and the
levels exceeded those that have caused reproductive
problems in dairy cows.
In conclusion, rust infestation reduced the nutritive
value and fermentation of corn silage, and resulted in
high levels of aflatoxin that made the silage unsafe to
feed. Inoculant application reduced adverse effects of
rust infestation on the fermentation and increased NDF
digestibility of clean and medium rust silages. In high-
rust silages, inoculant application also decreased mold
growth, increased aerobic stability, and prevented
aflatoxin production. Silages with no rust infestation
had high levels of zearalenone, suggesting that
mycotoxin binders may be needed when late-harvested
summer corn silages are fed to dairy cows in Florida.
Reference: Raid, R. and Kucharek, T. 2005. Florida Plant Disease
Management Guide: Sweet Corn. Report no. PDMG-V3-48, Department of
Plant Pathology, Florida Cooperative Extension Service, IFAS, University of
Florida. Accessed at http://edis.ifas.ufl.edu/PG054.
The authors are in the UF/IFAS Department of
Animal Sciences. Contact Gbola Adesogan at (352) 392-
7527 or adesogan@ ufl.edu.
Biogenergy from Manure
Ann C. Wilkie
Interest in manure digesters and associated energy
production is increasing, and new issues are arising
every day new technologies, regulatory hurdles,
financial incentives. The AgSTAR Program will hold its
next national two-day conference at the Baltimore
Hilton, in Baltimore, Maryland, on February 24-25,
2009. This conference is recommended for livestock
producers and others interested or involved in the
design, financing, operation, or regulatory oversight of
animal waste management systems, or in the
development of alternative sources of energy.
This year's conference will feature technical, policy
and financial presentations, poster sessions, networking
opportunities, and exhibits of the latest technologies
and services. For the latest agenda, hotel information
and to register online, visit the AgSTAR Conference web
page at http://www.epa.gov/agstar/conference09.html
is free of charge.
is an optional
meals fee of
$250. The AgSTAR Program is a voluntary effort jointly
sponsored by the U.S. Environmental Protection Agency
(EPA), the U.S. Department of Agriculture, and the U.S.
Department of Energy. The program encourages the use
of methane recovery biogass) technologies at confined
animal feeding operations (CAFOs) that manage manure
as liquids or slurries. These technologies produce
energy and reduce methane emissions while achieving
other environmental benefits. For additional
information about the AgSTAR Program, visit the
website at: www.epa.gov/agstar.
For questions or information about manure
bioenergy, contact Dr. Ann C. Wilkie at
firstname.lastname@example.org, (352) 392-8699, or visit the website
http://biogas.ifas.ufl.edu. Ann Wilkie is in the UF/IFAS
Soil and Water Science Department.
What Can DHIA Records Tell Us?
Daniel W. Webb
There are a lot of boxes and numbers on the monthly
DHIA herd summary. We are sometimes asked, "What
should I look at first to characterize my herd?" Almost
everyone will want to look at the rolling herd average or
the herd's pregnancy rate. However, we took a more
comprehensive approach for this article and chose the
top 20 items as key indicators of herd response to
We chose 8 herds from DHIA herds in Florida and
Georgia as examples to demonstrate the information
provided by these 20 indicators and to stimulate herd
owners to take a look at their own DHIA herd summary
for similar numbers.
The first 6 indicators indicate herd size and milk
production. Milk per day of first-calf heifers in the first
40 days and then in the next 60 days are good measures
of replacement program. The average weighted SCC
should be close to the bulk tank SCC average on test
day. Many veterinarians like to see 65% of the herd
below 150,000 SCC. Two of the herds in this table are
above this level. Pregnancy rate is one good indicator of
overall herd reproductive performance. Herds should
be above 15% for the year. Keeping track of the sex and
livability of newborn calves is the foundation of a
replacement program. Look at the numbers for these
herds. Most of the herds in this example are using
service sires of better genetic merit than either that of
cows or replacement heifers.
Contact Dan Webb at email@example.com or call (352)
Top 20 Indicators of Herd Response to Management from 8 DHIA herds.
Indicator A B C D E F G H
No. Cows 389 237 893 2385 1184 1187 2789 694
RHA Milk 21,883 20,296 25,059 22,463 17,530 17,722 21,067 22,140
TD Milk Ibs milk/ day 72 69.7 75.6 73.3 58.6 63.1 72.7 72.4
1st Lact <40 DIM Ibs milk /day 58 60 70 56 57 60 53 59
1st Lact 40-100 DIM Ibs milk /day 67 72 78 73 62 64 68 74
All 1st Lact Ibs milk / day 64 60 70 65 52 55 63 66
%Left Herd 43 33 32 38 34 30 31 35
Number Cows Died 12 15 54 197 29 64 211 43
Current weighted avg SCC 532,000 154,000 133,000 371,000 374,000 368,000 294,000 378,000
% Cows less than 142,000 SCC 45 77 77 52 49 53 60 54
Avg Days to 1st Service 73 101 77 91 73 78 77 85
Avg Pregnancy Rate 18 12 18 12 14 15 18 17
Services Successful last 12 months% 28 35 27 30 23 23 37 33
Male Calves Born Alive 183 98 1041 560 562 1324 304
Male Calves Born Dead 24 10 144 137 28
Female Calves Born Alive 225 100 442 1011 477 449 1263 351
Female Calves Born Dead 15 12 54 97 63 63 100 38
% Difficult Births (4+5) 7 .3 36 4 3 1 1
Avg Genetic Merit $ Sires of Cows 274 125 149 170 155 147 235 161
Avg Genetic Merit $ Sires of Heifers 360 168 289 302 357 379 344 282
Avg Genetic Merit $ of Service Sires 438 115 353 308 393 388 366 336
Florida Students Participated in 3rd Southern Regional
Albert De Vries and Mary Sowerby
A total of 54 students from 12 southern colleges and
universities participated in the third annual Southern
Regional Dairy Challenge, November 20-22, 2008 in
Statesville, N.C. North Carolina State University hosted
the 2008 contest, drawing participants from Alabama
A&M University, Berry College, Clemson University,
Ferrum College, University of Florida, University of
Kentucky, Louisiana State University, Mississippi State
University, North Carolina State University, Virginia
Tech, West Virginia University, and Western Kentucky
NORTH AMERICAN INTERCOLLEGIATE
DAiRV ChA IENGE
The Southern Regional Dairy Challenge is an
innovative two-day event designed by professionals
from allied industry and university educators to bring
classroom training to life in the real world for students
preparing for dairy careers. "The regional Dairy
Challenge, while offering a competitive format, is more
about educating students about dairy farm evaluation
and working with students from other universities,"
says contest planning committee chair Dave Winston of
Virginia Tech. "Students learn a great deal in the
process." A key objective is to present students with a
real-life situation that stresses the importance of
teamwork and professionalism.
Students arrived at the Holiday Inn conference
center on the afternoon of November 20. After check-in
and registration, participants were split into mixed-
university teams. Teams got to know each other over
dinner and then participated in team-building exercises
led by Dave Winston. Winston worked with students to
discover their teams' strengths and capabilities,
examine ingredients of effective teams, and evaluate
team members' personality styles. "I was impressed
with the camaraderie that developed among students
from different institutions after only being together for
such a short period of time," comments Winston. The
next morning, teams received detailed production,
financial, nutrition and reproduction records, and left
for their farm visit to evaluate cows, facilities and
management practices. After a two-hour farm visit,
teams returned to the hotel to analyze their data and
develop recommendations for improvement. Each team
prepared a 20-minute presentation that detailed their
observations and suggestions. The evening concluded
with dinner at the Iredell County Ag Center, following
by bowling at Statesville's Plamor Lanes.
On the program's final day, each team presented its
evaluation and recommendations to a panel of industry
judges. Teams were ranked as platinum, gold or silver,
based on how well they worked as a team and how
effectively their presentations of strengths and
opportunities for the dairy operation matched the
judges' evaluations. When teams were not presenting,
they toured the farm they had not evaluated for the
competition. The Dairy Challenge ended with dinner,
entertainment and an awards ceremony at Stamey
Farms in Statesville. Participants and coaches were
welcomed by Dr. Todd See, head of the Animal Science
Department at North Carolina State University, who
congratulated them on their excellent performance
throughout the event. Afterwards, most students
echoed the comments of one individual who said, "This
was a great program overall and had great experiences
that will benefit me in the future."
Major sponsors of the event were Select Sire
Power, American Dairy Science Association, Southern
States Cooperative, Genex, Dairy Farmers of America,
ABS Global, New Frontier Bank, Zinpro Performance
Minerals, Southeast DHIA, Agway Foundation, Merial
Ltd. and Dairy Production Systems of High Springs,
Florida. Contributing sponsors are recognized on the
Dairy Challenge web site http://dairvchallenge.org, as
well as in programs and news stories issued nationally
throughout the year.
Four University of Florida students with an interest
in dairy science participated: Candy Munz, Ashley
Massagee, Stephanie Croyle, and C.J. Middleton. They
prepared several afternoons during the fall of 2008 with
Albert De Vries. Mary Sowerby coached the students in
Statesville. The students did an excellent job and greatly
2nnrgrigtri thh Q\/gnt
From left: Stephanie Croyle, Ashley Massagee, Candy
Munz, C.J. Middleton, and Mary Sowerby at the third
Southern Regional Dairy Challenge. Contact Albert De
Vries at firstname.lastname@example.org or call (352) 392-5594.
The Dairy Business Analysis Project in 2009
Albert de Vries and Mary Sowerby
The Dairy Business Analysis Project (DBAP) was majorly
impacted in 2008 when Russ Giesy retired from UF/IFAS
in September. Russ had been working with DBAP since
its inception in 1996 when UF started collecting 1995
data. He has remained the driving force ever since. Russ
now runs Diamond Rule Dairy Management Consulting
Service and he remains interested in dairy business
analysis. Also, Dr. Lane Ely retired from the University of
Georgia in December 2008, but he has been hired back
part time. Part of Lane Ely's responsibilities will be to
continue DBAP for dairy producers in Georgia. Although
there is a commitment from the UF Deans to fill the
now vacant multi-county Dairy Extension position in
Central and South Florida, to our knowledge no action
has been taken.
What does this mean for DBAP in 2009? Mary
Sowerby will remain the primary contact person for
DBAP in North Central Florida. Lane Ely will remain
responsible for DBAP in Georgia. For the remainder of
the dairies, we contracted with Russ Giesy who will
work on data collection and reporting if the dairy
producer agrees. Producers may contact Russ directly to
have their data collected. UF/IFAS will get a copy of the
data once completed. Russ will have the full use of the
data he collects to the extent the producer agrees.
Because DBAP is a confidential program, we can no
longer grant access to the individual farm data Russ did
not collect, unless that particular producer agrees to
share it. Summary statistics such as averages calculated
by UF will be still available to anyone as in the past. The
contract with Russ includes a payment structure that is
in part made possible by a grant obtained by UF/UGA
last year from the Southeast Milk Check-off program.
Participation in DBAP allows dairy producers to
investigate their individual cost of production and
profitability, as well as identify strengths and
weaknesses. For 2009, we will focus more on the results
for the individual dairy producer, including comparison
with past results of the dairy. The focus on the
individual dairy producer means that a dairy producer's
report is ready as soon as his/her data collection is
completed. This individual cost of production analysis
could be performed multiple times per year and serve
as a basis for peer group discussions. We will still collect
2008 annual data for benchmarking and our annual
For more information about DBAP, contact Mary
Sowerby (email@example.com, 386-362-2771), Lane Ely
(firstname.lastname@example.org. 706-542-9107), Russ Giesy
(email@example.com, 352-669-0180), or Albert De Vries
How Well Can We Predict Future Milk Prices in
Albert De Vries and Shiferaw Feleke
"Prediction is very difficult, especially about the future."
Dairy producers take great interest in what milk prices
are going to be. For this first half of 2009, all indications
are that it is not going to be pretty. Low milk prices
strain cash flows and profitability.
Future milk prices are routinely predicted by USDA,
university professors, and CEOs. Nobody claims their
predictions are accurate and many realize their
predictions can be quite off from what the actual prices
are going to be.
Another source of information about future prices is
the milk futures market. Class III and Class IV milk
futures are traded daily at the Chicago Mercantile
Exchange for up to 24 months into the future. Contract
prices settle at the corresponding Class III and Class IV
cash prices announced monthly by USDA. The Class III
futures price reflects the market's expectation for the
Class III whole milk price for the month of production.
Another way to think about this is that traders try to
estimate what the Class III and Class IV cash milk prices
are going to be that will be announced by USDA a
number of months into the future. These traders are
typically well informed about supply and demand of
milk products, dairy expansions, fuel costs and
everything else that may affect future milk prices. The
announced Class III or Class IV cash milk prices by USDA
are directly linked to the calculation of the uniform
price in the Federal Milk Marketing Order 6 (Florida).
Thus, how well the futures markets predict future milk
prices is directly an indication of how well we can
predict milk prices in Florida.
Research by dairy economists has shown that the
milk prices predicted on the futures markets are on
average at least as accurate as milk prices predicted by
experts. But information about how accurate the milk
futures markets actually are is scarce. We decided to
look at the data.
Our study assessed the accuracy of 3 methods that
predict the uniform milk price in Federal Milk Marketing
Order 6. Predictions were made for 1 to 12 months into
the future. Data were from January 2003 to May 2007.
The CURRENT method assumed that future uniform
milk prices were equal to the last announced uniform
milk price. This is a native prediction method. The
F+BASIS and F+UTIL methods were based on the milk
futures markets because the futures prices reflect the
market's expectation of the Class III and Class IV cash
prices that are announced monthly by USDA. The
F+BASIS method added an exponentially weighted
moving average of the difference between the Class III
cash price and the historical uniform milk price (also
known as basis) to the Class III futures price. The F+UTIL
method used the Class III and Class IV futures prices, the
most recently announced butter price, and historical
utilizations to predict the skim milk prices, butter fat
prices and utilizations in all 4 classes. Predictions of
future utilizations were made with a Holt-Winters
smoothing method (a useful method to predict trends
over time). Federal Milk Marketing Order 6 had high
Class I utilization (85 4.8%). Mean standard
deviation (a measure of variation around the mean) of
the Class III and Class IV cash prices were $13.39
2.40/cwt and $12.06 1.80/cwt, respectively. The
actual uniform price in Tampa, Florida, was $16.62
2.16/cwt. The basis was $3.23 1.23/cwt. The F+BASIS
and F+UTIL predictions were generally too low during
the time period considered because the Class III cash
prices were higher than the corresponding Class III
futures prices. Figure 1 shows the Class III futures
markets and the actual announced Class III price by
USDA for the same month of production. For the 1- to
6-months ahead predictions, the root of the mean
squared prediction errors (RMSE, a standard measure of
accuracy) from the F+BASIS method were $1.12, $1.20,
$1.55, $1.91, $2.16, and $2.34/cwt, respectively. The
RMSE ranged from $2.50 to $2.73/cwt for predictions
up to 12 months ahead. Results from the F+UTIL
method were similar (Figure 2). The accuracy for the
F+BASIS and F+UTIL methods for all 12 forecast horizons
were not significantly different (they could be the
same). No method included all the information
contained in the other methods.
So what does this mean? In conclusion, both
F+BASIS and F+UTIL methods tended to more accurately
predict the future uniform milk prices than the
CURRENT method, but prediction errors could be
substantial even a few months into the future.
"Substantial" means that we can be only 68% confident
that the actual uniform price is within the predicted
price plus or minus $2/cwt, even only 5 months into the
future. We can be 95% confident that the actual price is
within plus or minus $4/cwt from the predicted price
even only 5 months into the future. Of course, these are
very large ranges; hence "prediction is very difficult
especially about the future". One might as well use the
long term average uniform milk price to predict milk
prices more than 6 months into the future (perhaps
adjusted for inflation). For predictions less than 5
months into the future, the uncertainty was less. The
majority of the prediction error (70%) was caused by
the inefficiency of the futures markets to predict the
Class III cash prices. Other sources of prediction error
were uncertainty about future utilizations and butter fat
prices. Unfortunately, none of this means that we
cannot have low milk prices the first half of 2009.
The study appeared in the December 2008 issue of
the Journal of Dairy Science. Contact Albert De Vries at
firstname.lastname@example.org or call (352) 392-5594.
I I I I I I I I i t I t i I I I I I I
Figure 1. Class III futures prices for contracts (o) 1-month ahead, (o) 3-months ahead; (A) 6-months ahead, and (0) 12-
months ahead, (0) Class III prices announced by USDA. Average monthly prices from January 2003 to May 2007 (De
Vries and Feleke, 2008).
C> C; i C)? 0 C 0 C) C; 0 C) Ca
Figure 2. Predicted uniform milk prices for Federal Order #6 (Florida) based on the Class III and IV futures prices, and
predictions for butterfat prices and utilization(F+UTIL method): (n) 1-month ahead, (o) 3-months ahead; (A) 6-months
ahead, and (0) 12-months ahead, (0) actual uniform milk price in Federal Order #6. Average monthly prices from
January 2003 to May 2007 (De Vries and Feleke, 2008).
Upcoming Dairy Meetings
* January 28-29, 2009: 35th Annual .
Southern Dairy Conference in Atlanta, '
Georgia. Further information: call 706-
583-0347 or email email@example.com.
* February 10-11, 2009: 20th Florida Ruminant
Nutrition Symposium in Gainesville, Florida.
* Dairy Road Show, TBA. Probably early March.
* April 28, 2009: 46th Florida Dairy Production
Conference in Gainesville, Florida.
For more information and registration,
http://dairy.ifas.ufl.edu or contact Albert De
Gators National Football
Dairy Update is published quarterly by the Department of Animal Sciences, University of Florida, as an educational and informational service. Please address any
questions or comments to Albert De Vries, Editor, Dairy Update, PO Box 110910, Gainesville, FL 32611-0910. Phone: (352) 392-5594. E-mail: firstname.lastname@example.org. Past
issues are posted on the UF/IFAS Florida Dairy Extension website at http://dairy.ifas.ufl.edu. This issue was published on January 21, 2009.