One of the Best Uses of Big Data
While the uses of big data may seem sketchy and only involved with
money, there’s way to use this information to feed starving populations.
India has millions of acres that could be worked on, but the land is worked
on by individual farmers that cannot use or collect vast amounts of data.
There
are companies, like CropIn, that think big data analysis can help find
ways to optimize the agricultural process. Indian farmers could especially
benefit from that kind of data analysis that would allow them to make better
decisions when it came to their crops.
How Trustworthy is Big Data?
Farmers put their entire business at stake every year. If their yield is low or
crops are destroyed by natural disasters, then the
farmer and their family are
in trouble. This makes farmers slow to trust anyone when it comes to their
crops. Trusting big data analysis might be too hard for some farmers
because of how vague it is.
Companies that provide big data analysis, like Monsanto, are hated by
much of the world for scandals that could be responsible for damaging and
poisoning our food. This leads to even less trust of big data. Because of all
the mistrust, it will take a long time before big data
and agriculture are fully
integrated together. Big companies will have to spend a long time
convincing farmers to trust them, especially since the companies are so
demonized right now.
Sooner or later, the world of agriculture will be improved by big data. It
will happen eventually, but it may take a lot of time.
Can the Colombian Rice Fields be saved by Big
Data?
There is one specific place in the world where big data could improve the
agriculture of a whole nation.
In Columbia, there are rice fields that have
been facing inexplicable decreases in yields over the overs. They had
actually been having increases in yields until 2007 where the decline
began. Regardless of what they tried, they could not stop the decline.
For a while, climate change was declared the main culprit of the decline,
but no one could find evidence that it was that. In fact,
no one could figure
out what exactly was the cause. Although there were concerns about
sharing the data on the rice fields’ yields, government agencies began
surveys and had data collected.
From the analysis of the data, they found several ways to consider what was
happening to the field. These inferences varied from region to region, but
they could now at least take a guess at the cause. The city of Saldana
appeared to have less daily sunlight and that was decreasing yields.
However, the city of Espinal wasn’t keeping up
with the increasing nightly
temperatures. With this information, farmers could adjust to the needs of
their individual regions. What was going to help in Saldana wasn’t going to
help Espinal and vice versa.
The way that data analysis was used here could revolutionize the industry.
If this method was used in the entire world, then all fields could be
optimized and we could feed more people more efficiently. Using big data
analysis for crops is likely to feed more of the world with less cost. It’s a
win for everyone.
Up-Scaling
Big data
has been shown through small, successful projects to be able to
help farmers. However, that data needs to be taken to agriculture in a larger
way. In future years, more and more companies will be analyzing
agricultural data. In turn, more farmers will be
able to use the information
to increase their yields and profits.