How Big Data Is Trying To Create a Perfect Tree

Nothing matches the warmth of a Christmas tree at the year end. The biggest symbol of the holiday festivities allows even dysfunctional families to have a get-together. However, very few people know that scientists are trying to solve a vexed problems related to the plant.

It’s a big business

More than 350 million natural Christmas trees are harvested in the 50 U.S. states. In 2013, more than a billion dollar worth Christmas trees were sold in the U.S homes in 2015, according to an estimate of National Christmas Tree Association. There are more than 15000 Christmas tree farms in the U.S. and all of the Christmas trees come from these farms only.

The madness about the Fraser fir

If Fraser Fir is considered the finest variety of Christmas tree—it’s not without a reason. It has a perfect triangular shape, a genuine piney fragrance and the leaves have softer needles. The problem, however, is: when the new year approaches, its quality starts going down. The smell of beautiful saplings start turning into decomposing wood; and the beautiful needle-shaped leaves litter on the floor. This also means the loss of business for many shoppers.

How Big data will help?

Scientists are trying to refine the breeding of Christmas trees and understanding the ways to grow a high- quality variety of Fraser Fir. A government funded initiative started at UConn, the University of Connecticut where plant scientists along with data-scientists will work to develop a perfect Christmas tree with the help of data scientists.

The team will use a software that will have genetic, physical and other kind of more than 15 plant varieties under the guidance of Jill Wegrzyn, Department of Ecology and Evolutionary Biology. The team is trying to create tools for the benefit of crop sciences with the help of big data models.
The path is not easy

While talking to New Scientist Magazine, “It’s one of the ongoing hurdles of data analysis. As a scientist, I might be aware of these important data sources, but they are in different formats and locations, and are often much too large for a single desktop machine to analyze,” said Wegrzyn. “Getting access to so much of data is really challenging. The role of bioinformatics becomes critical in the next-generation genome sequencing and phenotyping.

How things are moving?

Wegrzyn and her colleagues, including project principal investigator Stephen Ficklin at Washington State University, recently received $1.5 million from the National Science Foundation to develop a cyber infrastructure, called Tripal Gateway, that will allow scientists to access, visualize, and analyze data anywhere in the world. The infrastructure builds on Tripal, an existing open-source toolkit designed to assist with the construction of online genomic and genetic databases. It will serve thousands of scientists from industries, universities, and nonprofits worldwide; and is the part of the $31 million program of the NSF Data Infrastructure Building Blocks program.

Many people think of big data in the life sciences as solely genetic information, but Wegrzyn points out that many scientific databases also contain large amounts of phenotypic data, or information about the physical attributes of organisms, as well as environmental data.

However, things are gradually becoming easier with the development of other technologies such as drone technology which is helping out gather data from forests and orchards. So, we can hope a better quality Christmas tree by the end of next year.


Chief Content Strategist

An active journalist and blogger with more than a decade of experience. He has worked with various national and international publications. Sharing behind the curtain news is his passion.

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