Data science in agriculture

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Data Science in Agriculture
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Data Science in Agriculture Saving the lives
of farmers
Agriculture is the most important sector of the
Indian economy, that provides employment to
almost half the population of the countrys
workforce!! India is the second-largest producer
of fruits and vegetables in the
world. Agriculture is the backbone of Indian
economy, still, it suffers from a heaping number
of disasters such as climate change,
unpredictable monsoon or lack of it, droughts,
floods, migration of farmers towards the cities
in search of better-paying jobs, and more.
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Data Science Applications in
Agriculture
Here are the six applications of data science in
agriculture sector
1. Digital Soil and Crop Mapping This is
related to building digital maps for soil types
and properties. Some people in the agricultural
industry manage so many acres of land, its
almost impossible to get prompt updates and
alerts about potential problems without help
from technology.
2. Weather Prediction Weather plays a very
important role in agriculture production and has
an influence on the growth, development, and
yield of crops. Weather aberrations can cause
physical damage to crops and soil erosion.
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2. Weather Prediction Weather plays a very
important role in agriculture production and has
an influence on the growth, development, and
yield of crops. Weather aberrations can cause
physical damage to crops and soil erosion.
3. Fertilizers Recommendation
Weather plays a very important role in
agriculture production and has an influence on
the growth, development, and yield of crops.
Weather aberrations can cause physical damage to
crops and soil erosion.
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4. Disease Detection and Pest Management tion In
modern agriculture, advanced algorithms are
used to identify the patterns and behavior of
nature that helps in forecasting the invasion of
pests and the spread of microscopic diseases.
5. Adaptation to Climate Change
Climate change is a looming concern that has
already affected the agriculture sector.
However, data science experts are working hard
to figure out ways to compensate for the change.
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6. Automated Irrigation System
We can also use weather prediction in the
automated irrigation system. How exactly? Having
a system that tells you the soil is dry but you
dont need to irrigate because it is going to
rain after a few hours seems to be an
interesting use case.
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Summary

• These were just a few cases showing how one can
  use data science in the work of an agricultural
  corporation right now because, in the future, we
  cannot predict what opportunities it can bring.
  Technology has played a huge role in developing
  this industry.
• Today, it is possible to grow crops in a desert
  by use of agricultural biotechnology and there
  is much more scope in the future.

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Thank You
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