Data science can provide actionable insights bespoke to farmers' land and ownership patterns on what to plant when to plant, and what farm practices to deploy. Making well-informed decisions could save costs and enhance a farmer's profitability and income.
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2. 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 country’s
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.
3. Here are the six applications
of data science in agriculture
sector:
This is related to building digital maps
for soil types and properties. Some
people in the agricultural industry
manage so many acres of land, it’s
almost impossible to get prompt
updates and alerts about potential
problems without help from
technology.
1. Digital Soil and Crop
Mapping
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.
Data Science Applications in
Agriculture
4. 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.
2. Weather
Prediction
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.
5. 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.
4. Disease Detection and Pest
Management
tion
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.
6. 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 don’t need to
irrigate because it is going to rain after a
few hours seems to be an interesting
use case.
7. 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.
8. Thank You
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