October 12, 2008
Contacts: Larry Chase, Cornell University, 607-255-2196; Cornell
Cooperative Extension: Clinton/Essex counties: Anita Deming,
518-962-4810; Franklin: Carl Tillinghast, 518-651-6321, Jefferson: Ron
Kuck, 315-788-8450; Lewis: Frans Vokey, 315-376-5270; St. Lawrence:
Brent Buchanan, 315-379-9192
NNY Project Sets Basis for Statewide Evaluation of Factors
Affecting Milk Premiums Paid to Farmers
At the store, consumers have several milk purchasing options – white
milk, chocolate milk, whole milk, two percent, skim… On the farm, dairy
producers are constantly evaluating options to increase milk production
and quality. Various components, such as milk fat and protein, equate to
milk check premiums. With funding from the Northern New York
Agricultural Development Program, dairy farmers in the North Country,
Cornell University researchers and Cooperative Extension educators have
evaluated ways to improve the production of milk components. Additional
funding from Cornell is now expanding this project statewide.
Project leader and Cornell University Professor of Animal Science Larry
E. Chase says, “Milk components are critically important in determining
the size of producers’ milk checks, and a large number of factors affect
component levels. We worked with dairy farmers in Northern New York to
begin learning why component levels differ so much from one herd to
Milk component pricing fluctuates. A Cornell University survey by Dr.
Mark Stephenson indicated the percentages of milk components were
slightly lower in Northern New York than in other regions of the state.
An analysis of 218 milk checks from 181 Northern New York dairy farms
showed the region’s farmers consistently received the lowest premiums.
Chase led a research team that evaluated feed, water and milk samples
from 52 Holstein dairy herds in Northern New York’s six counties:
Clinton, Essex, Franklin, Jefferson, Lewis and St. Lawrence. Cornell
Cooperative Extension educators in each county helped select herds for
the project and with on-farm data collection. An initial analysis of the
data collected from the Northern New York dairy herds evaluated single
factors that influence the milk fat or protein content of milk. Chase
says, “We did not find a significant relationship between either the
number of cows per herd or herd daily milk production and milk fat/milk
The selected herds were all fed a total mixed ration diet and had daily
milk production of greater than 65 pounds of milk per cow per day with
an average of 76 lbs/cow/day. Factors related to higher milk fat levels
(and by extension milk check premiums) were feeding a larger corn silage
particle size and a higher NDF (neutral detergent fiber for
digestibility) content in the corn silage. A higher ration starch NFC (nonfiber
carbohydrate) level was associated with higher milk protein levels.
Chase is quick to say, “We cannot say this data represents a specific
cause and effect relationship. We want to add more dairies in other
areas of New York to broaden our database before drawing any conclusions
that would lead producers to change their production practices.”
Additional analyses are now being conducted with the NNY dairies’
dataset using a multi-factor approach and additional funding from
Cornell University is expanding the research statewide.
The extended project results, expected by September 2009, will be posted
on the Northern New York Agricultural Development Program website at
www.nnyagdev.org with other dairy industry articles, fact sheets,
research reports and resource contacts.
In addition to Chase, the research team for this Northern New York
Agricultural Development Program project included Associate Professor of
Animal Science Thomas R. Overton, Research Support Specialist Charlene
Ryan, and undergraduate student James Tauzel of Cornell University; and
William Stone, DVM, with Diamond V Mills, an animal feed maker.
The Northern New York Agricultural Development Program is a
farmer-driven program that funds research, education and outreach for
farmers in Clinton, Essex, Franklin, Jefferson, Lewis, and St. Lawrence
counties. # # #