1. OVERVIEW
Cowscope is designed to help farmers better manage mastitis on their farms. Over the
course of six months, we taught ourselves Stanford University’s Design Thinking method,
consulted a dozen local farmers, and went through numerous revisions to build an app and
microscope attachment with maximum impact in detecting bovine mastitis and providing
useful data for tracking trends in cow health.
Cowscope is made up of three sections: the Somatic Cell Counter with on-the-farm mobile
microscope attachment, the Cost Calculator, and Cow Data. Each section focuses on a
different part of management for mastitis: detection, individual cow analysis, and overall
herd analysis.
SOMATIC CELL COUNTER
The Somatic Cell Counter seeks to speed up the cell-counting process by bringing the lab
to the farm.
Somatic cells are the cells from the body of the cow that end up in the milk. The dairy
industry is extremely strict about the concentration of these cells that can be in the milk
farmers sell, and milk is thrown out if the somatic cell count (SCC) is too high. Cows with
mastitis have a highly increased somatic cell count, and thus it is of huge importance to the
farmers and consumers to quickly identify the cows with mastitis and have an accurate
somatic cell count before giving the milk to the quality regulators testing the SCC for
human consumption. If the SCC is too high in a tank of milk, it is thrown out, and the
farmer loses the entire income of the batch [1].
Cowscope
A COW-SIDE SOMATIC CELL COUNTER AND DATA LOG
Sachiye Koide, Amanda Ong, Monica Ong

2. Images by Amanda Ong.
According to the farmers and researchers we met with, the only way for farmers to get a
quantitative SCC for each of their cows is to send the milk to facilities where lab
technicians can analyze the samples. This can take between 18 hours and several days,
according to Dr. Daryl Nydam, Director of Quality Milk Production Services at the Cornell
University College of Veterinary Medicine. In New York State, where there is a huge
emphasis on agricultural research, many farms are fortunate enough to only be an hour
away from the nearest facility. However, farms in more rural areas as well as in the west
and mid-west often live much further away. Because it can take very long to package and
transport samples and wait for the results, farms can only check the SCC of their cows
once a month. Since it’s inefficient to check the SCC for a few individual cows, this is often
neglected. Many farms may instead opt to have a technician come to their farm once a
month to check the SCC of each cow in their herd. Overall, the process is time consuming,
infrequent, and expensive [2].
One of the ways lab technicians get the SCC is through direct microscopy using a dark
blue L-W stain on the nuclear mass and a hemocytometer [3]. They recognize the nuclear
masses in the hemocytometer grid and manually count them to get the average [3]. Our
solution intends to bring that process from the lab to the dairy farms.
We created an inexpensive, 3D printable, customized cow-side microscope that utilizes a
smartphone camera to take the somatic cell count within our app. We collaborated with

3. iGEM Cambridge JCC 2015 to get their feedback from working on project Openscope,
and ultimately decided on a more mobile design for carrying around the farm.
Cowscope images and design by Sachiye Koide.
Our microscope uses a simple light, 30 mm lens, and smartphone camera to take pictures
within the app of samples placed in a hemocytometer on the plexiglass surface. In this
section of the Cowscope app, farmers can image their samples and save their microscope
photos in one place for fast, efficient somatic cell counting. Soon, we will be adding a
photo recognition feature which uses the same parameters the lab technicians use to
recognize count the stained somatic cell nuclear masses within the top and left borders of
the hemocytometer grid. [3]
The Somatic Cell Counter will not only allow farmers to take and save their cell images, but
photo-recognition software of the stained nuclei will allow the app to take the cell count
for the farmer, eliminating the need for the time-consuming individual counting. It will
then calculate the SCC concentration, and add the information to the Cow Data section
that keeps track of individual cow health and history.

4. COST CALCULATOR
The Cost Calculator aims to give farmers some quick metrics to weigh the potential
financial costs of an infected cow. The Keep page allows farmers to calculate the cost of
keeping the cow. As a preliminary simplification we have included factors such as
treatment time, milk production, and milk cost, but we acknowledge that there are more
factors that determine the cost of taking care of an infected cow. The Discard page acts
like the Keep page, except it takes in factors that determine the cost of “letting go of” or
culling the cow. Finally, after inputting the data, the app will highlight the less costly
option in green, which farmers can use in their decision for treating an infected cow.
Images by Monica Ong
COW DATA
The Cow Data section shows farmers trends that may be overlooked in the day-to-day care
of farms. It shows graphs such as infection by cow and milk production so that farmers can
identify clusters of cows that have recurring infections, and see how productive each cow
is. We intend for the Cow Data section to highlight trends such as budding mastitis
outbreaks, so that farmers can take preventive measures as early as possible. This section
was created at the enthusiasm of farmers we talked to about the idea, and we will continue
expanding the scope of the Cow Data application in order create as holistic a picture of the
disease on the farm as possible. Soon we may be able to compare other local farm data to

5. identify regions where outbreaks are more common and may begin affecting other farms.
Our goal is to create a local, regional, and even national network to identify trends in
disease and create the foundation for more regionally targeted and efficient cures.
[1] Reneau, Jeffrey K. Somatic Cell Counts: Measures of Farm Management and Milk
Quality. N.p.: National Mastitis Council, 2001. Pdf.
[2] Nydam, D. (2016, May 13). Personal interview.
[3] Direct Microscopic Somatic Cell Count Guideline. (n.d.). Retrieved October 18, 2016,
from https://foodsafety.foodscience.cornell.edu/sites/foodsafety.foodscience.cornell.edu
/files/shared/documents/CU-DFScience-Notes-Milk-Somatic-Cell-Counting-06-10.pdf
https://foodsafety.foodscience.cornell.edu/sites/foodsafety.foodscience.cornell.edu/files/
shared/documents/CU-DFScience-Notes-Milk-Somatic-Cell-Counting-06-10.pdf