Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Better ways of using Analytics in Agriculture in india


Published on

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.

Published in: Data & Analytics

Better ways of using Analytics in Agriculture in india

  1. 1. Better Ways of Using Analytics in Farming in India Pratik Patil Yagnesh Shetty
  2. 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: 2 – Cropping up on every farm: 3 – Big Data Across Agriculture:
  3. 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 : 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. 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: 2 – Big Data Across Agriculture: 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. 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. 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: 2 – CropIn: 3 – KisanHub: 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. 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. 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..