There is a great deal of variability in the shape of individual lactation curves, but until now tools for quantifying that variability have been very weak. With MilkBot® technology, several new approaches to understanding changes in milk production become possible.
The most immediate MilkBot® product is fitted
parameter values, generated by the fitting
engine. This in turn allows statistical
analysis of possible relationships between other variables and
parameters. Parameter values can be generated by us
from almost any data set containing milk weights and returned
to you for use in various ways. We can also
calculate residuals at each data point, and provide you with software
to calculate lactation curves from parameter values.
Are the cows up or down on milk?
Almost everything we try to control in managing a dairy herd,
including health, feeding, environment, breeding, and milking, will
influence daily milk production. Quantifying changes in milk
production is complicated by large variability which can easily hide an
important economic effect in random noise. For example, we
might make a ration change which costs $0.25 per cow per day.
Did milk production increase enough to recoup that cost? Is
it a profitable decision?
This type of question is extremely common, in management of individual herds as well as in dairy research. Because of the nature of tests used in statistical inference, our ability to make a statistically valid conclusion in questions of this sort is proportional to the number of animals in the trial, the size of the expected response, and the amount of random variability, or variability that cannot be explained by a known valid model. Even without formal training in statistical methods, common sense and experience face the same limitations. In the case of the $0.25 feed change, it is unlikely that we can reliably answer the question whether or not it pays, because we won’t have a large enough trial to detect the small expected milk increase which is likely to be obscured by normal variability in daily milk production over the several days or weeks that the change in ration will take to reach its full effect. The economic consequences are not small, though, because $0.25 per cow per day becomes $9,000 for a group of 100 cows over a year. Yes or no, it could be a costly guess.
This daily variability in milk production has several causes, including cows entering and leaving the milking group, and the normal rise then fall of daily production after calving, the “normal lactation curve”. A standard technique for decreasing random variability, and increasing the power of statistics, is to develop and validate a model which can explain a portion of the observed variation, MilkBot allows a very sophisticated approach to this general problem set, significantly increasing the precision with which we measure changes in milk production
It is probable that many factors influence scale, ramp, and persistence of individual lactations, including genetics, transition management, feeding, and environment. MilkBot® allows us to use standard graphical and statistical tools to study those associations. For example, the two charts below show scale and persistence for about six million lactations, averaged by previous-days-dry (pdd) for the previous lactation. There are some complex issues in interpreting this data, but it is clear that MilkBot® has been able to pull out patterns that suggest some interesting hypotheses.