In 2017 researchers at Cornell University and Miner Institute introduced a new test to analyze the composition of fatty acids that make up the milk fat test.  By knowing the composition of fatty acids as a percent of the total fatty acids, dairy producers and consultants can make more informed decisions about what factors may be impacting the fat test and cow health.  Follow this link to see an article I wrote about a year ago explaining the test;


To briefly summarize that article, the fat test can be broken down into three groups of fatty acids: de novo, mixed, and preformed.  De novo fatty acids are the short chain fatty acids and are completely synthesized in the rumen; they range in length from 4 to 14 carbons long and can be used as an indicator for rumen health.  Preformed fatty acids are the long chain fatty acids and come from dietary fat and mobilized adipose tissue; they are 18 or more carbons long and can be used as an indicator for energy balance.  Mixed fatty acids are 16 carbons long and come from both rumen synthesis and preformed sources.


If a farm is willing to invest in sampling for fatty acid composition ($30 for up to 10 samples), we should know how to interpret and use the results to help improve the milk fat test.  This led us to conduct a small study to evaluate how changes made on farm could impact the fatty acid composition – specifically the amount of de novo fatty acids on a percentage basis.  We decided that we wanted to follow two farms for one year, and we were going to sample every load of milk that left each farm.  We were also going to track changed in stocking density, milk yield, diet composition, and weather.  One year and 1108 samples later, we finally have some results to share.


To keep anonymity, the two farms will be referred to as Farm A and Farm B.  Throughout the time we were following the farms, Farm A averaged 89 pounds of milk with a 4.21 fat test and 3.25 protein test.  Farm B averaged 74 pounds of milk with a 3.92 fat test and 3.24 protein test.  Factors associated with changes in the de novo fatty acid percent on Farm A were milk yield, dietary levels of NDF from forage, rumen unsaturated fatty acid load, and T10-C12 CLA, temperature, temperature humidity index, and day length.  Factors associated with changes in the de novo fatty acid percent on Farm B were stocking density, bunk space per cow, temperature, temperature humidity index, and day length.


The factors that were consistent between both farms were temperature, temperature humidity index and day length.  These indicate that the fatty acid composition follows a seasonal trend along with the fat test.  The factors that were not observed on both farms are milk yield, stocking density, bunk space per cow, and several dietary factors.  Because these factors were not observed on both farms, we can speculate that there are different levels of genetic potential and management on both herds.  This also makes it difficult to apply a one size fits all recommendation for the fatty acid composition.


Although it did not show up in our statistical analysis, we did observe some short-term changes in composition when feed changes were made such as switching haylage crops or corn silage bunkers.  Extreme heat stress events did not appear to alter the composition, although this could be since both farms have mechanically ventilated barns (Farm A – tunnel ventilation, Farm B – cross ventilation).


In conclusion, we determined that fatty acid composition is difficult to use as a predictive tool due to all the factors that have an influence on fat test.  At the cost of $3 per sample, we did not feel like we were learning any more than we could from looking at the creamery fat test.  There is some limited research looking at individual cow data that could potentially be beneficial to dairy farmers, but we will have to wait until that becomes available.


by Lee Kloeckner