Received the 1st Prize for this Research Paper presentation on Better Ways of using Analytics in Agriculture in India. Undertook Primary and Secondary Research to understand innovations in the agricultural sector that could transform the productivity levels and yeild/hectare for Indian farms. Did a comparative study of the Global scenario and made recommendations for Indian scope.

1. Better Ways of Using Analytics in
Farming in India
Pratik Patil
Yagnesh Shetty

2. Why Analytics in Farming?
• As we gear up to become home to 9.2 billion people by 2050, economies are also
preparing to increase their food production by almost 70% 1
• 500 million farmers, adding up to roughly a billion acres 2
• Decisions still taken on experience and judgement and not on data
• Many crops – rice, wheat, pulses, potatoes, sugarcane, oilseeds and non food items such
as cotton, tea, coffee, rubber, jute, etc
• Low yields/hectare of crops, improper water management
• 1/5th of Land Output lost
• In Agri business, Big Data can help improve crop yield, drive agility/responsiveness,
manage risk and align to demand by answering questions that were practically impossible
to address a few years ago 3
• In today’s world of the health and wellness consumer, where commodity risk
management and compliance are critical, Big Data can be unlocked to make accurate,
predictive and timely decisions across the Agri value chain 3
1 – Big data and Agriculture: http://www.mahyco.com/knowledgezone/downtoroots/41/big-data-and-agriculture.html
2 – Cropping up on every farm: http://fortune.com/2014/05/30/cropping-up-on-every-farm-big-data-technology/
3 – Big Data Across Agriculture: http://www.wipro.com/blogs/big-data-across-the-agriculture-value-chain/

3. Analytics in Farming over the
World
Precision Agriculture
• Sensors can tell how effective certain seed and types of fertilizer are in
different sections of a farm
• Software will instruct the farmer to plant one hybrid in one corner and a
different seed in another for optimum yield
• It can adjust nitrogen and potassium levels in the soil in different patches
Big data is taking over the farm : http://www.businessinsider.com/big-data-and-farming-2015-8?IR=T
US farms generate $375 billion from
crops
Almost all new farm equipment is
equipped with sensors
60% of farmers report using some sort of
precision data
Farmers say data analytics have reduced input
costs by 15%, Crop sales are up by 13%
Next Steps
Data from thousands of farms
is collected, aggregated, and
analysed in real time
In the same way that Google can identify flu outbreaks
based on where web searches are originating, analysing
crops across farms helps identify diseases that could ruin
a harvest

4. Analytics in Farming in India
Past
• Traditionally, farmers have been “on their own” managing their land
• Hit and Trial method of sowing
1 – Cropping up on every farm: http://fortune.com/2014/05/30/cropping-up-on-every-farm-big-data-technology/
2 – Big Data Across Agriculture: http://www.wipro.com/blogs/big-data-across-the-agriculture-value-chain/
Future
• Access the data in real-time for analysis and get it right the first time
• Despite the availability of data, the Agri sector does not make liberal
use of it 2
• Data can be churned effectively using analytical software technology
to map information on parameters like monsoon trends, soil quality,
use of pesticides etc. and convert them into meaningful information
1
Real-time Data from
farms and cloud
algorithms
Run the big-data
analytics in real
time
Let farmers get
all the right
math on their
fingertips

5. Primary Research
20%
80%
Do you own a smartphone?
No
Yes
• None of the farmers had a 100% produce
• 3 out of 5 farmers were confident
that understanding the quality of
soil would benefit them 0 1 2 3
Depending on current produce
Experience of past few years
Lab Testing
Try to predict the quality depending
on the quality of previous produce
How do you gather information about your soil and
crops?
• Only 1 out of 5 farmers were willing to share data if it would guarantee a better
produce with one not sure about sharing data. The reason understood was the lack of
information about the services/analytics
• All of the farmers have experienced wastage of
raw materials to a certain extent

6. Challenges
• India probably not equipped for something like big data in agriculture yet 1
• Small farms in India as opposed to large farms abroad India make it difficult to use
analytics effectively
• The average Indian farmer is already cash strapped to afford such a luxury
• The willingness of farmers about sharing data
1 – Big data and Agriculture: http://www.mahyco.com/knowledgezone/downtoroots/41/big-data-and-agriculture.html
2 – CropIn: http://cropin.co.in/home.html
3 – KisanHub: https://www.kisanhub.com/
The Path Forward
• Government pitch in with private agri companies
• Jump the gun with directly going for aggregation of farms
• Apps such as CropIn and KisanHub are moving towards providing
analytical data on the phone 2 3
• Creating awareness amongst farmers about Analytics and its
services

7. Appendix
Do you
own a
smartpho
ne?
How often
do you
have a
100%
produce?
Do you think you
would benefit if you
understood the type
of soil, the type of
crops that could be
sowed?
How do you gather
information about
your soil and crops?
How often do you
encounter wastage
of seeds/raw
materials after a
produce?
Would you be willing
to share data about
your soil quality and
crops if it would
guarantee a better
produce?
Yes Never Maybe
Experience of past
few years Quite often Maybe
Yes Never Yes
Try to predict the
quality depending on
the quality of
previous produce Always No
Yes Never Yes
Experience of past
few years Always No
No Never Yes
Depending on
current produce Always No
Yes Never Maybe Lab Testing Sometimes Yes

8. Thank You!
Questions?
Imagine a time when farmers can grow crops that fit beautifully with what nature has to offer. When
farmers know in advance when it will rain, and when they will benefit from low costs of production.
Big Data analytics ensures that such structured and systematic interventions can be achieved sooner
than later..