Leveraging Bigdata in Agriculture

What is the most basic human need for survival? The simple answer is FOOD.


Healthy and sustainable food systems are necessary for the development of world economies. And how do you ensure an uninterrupted supply of food commodities? It is most definitely through Agricultural development.


Agriculture contributes to 4% of the global GDP and for some developing nations, this figure can rise to as high as 25%. And did you know – Livelihoods of 65% of the poor working adults across the globe, depend on Agriculture.


These numbers and data indicate – Agriculture is crucial to the world’s development goals. A lot is already happening to bring about a change in the way the Agricultural sector operates – one thing being the use of Big Data in Agriculture.

So, what is Big Data in Agriculture?

Big data in agriculture refers to a massive volume of real-time, structured, and unstructured data that is collected by the Agricultural industry on an everyday basis.

How can the agricultural sector leverage Big Data?

With agriculture holding a dominant share in the world’s economies, it is obvious that massive amounts of data need to be collected, stored, and analyzed every day.


Data experts, after using various big data analytics tools, share relevant information with the primary stakeholders of the sector, i.e., farmers. The farmers then use this information to improve their productivity and output, which contributes to their profitability.


Let us look in detail – How the use of big data in Agriculture facilitates the farmers?

How Big Data in Agriculturehas opened doors for development at the farm level?

Big data in Agriculture is an effective application of technology in Agriculture. Various apps, sensors, satellite-based images, and other big data analytics tools are used so that farmers can devise methods that will help them reduce costs and increase productivity.


Big Data and data analytics facilitate farmers in so many ways:

1.It has helped enhance farming techniques and methods

What Big Data in Agriculture does is, it collects and stores historical and real-time structured and unstructured data, and post its analysis sends vital, real-time information to the farmers.


This information has to do with the following:

  • Weather and monsoon forecasting
  • Pest & fertilizer management
  • Mineral and moisture levels in soil
  • Plant health
  • Intercropping decisions, if necessary, i.e., changing the crop altogether owing to the weather and soil conditions, etc.

This information helps farmers take appropriate decisions regarding:

  • Soil preparation,
  • Which crop to sow, and when?
  • Regulated use of pesticides and chemicals
  • Selecting Hybrid Crops
  • Harvesting crops
  • Price forecasting, etc.

With the help of Big Data Applications, farmers can also track the routes of machinery being used in the fields. This information helps them to optimally utilize their machines, hence saving on the fuel cost.


With all these in place, farmers can rest assured of:

  • Reduced production cost
  • Higher productivity
  • Increased profitability

2.Big Data in Agriculture also helps farmers take crucial decisions by:

A. Forecasting commodity prices
B. Sharing the current commodity prices

A. Forecasting the agricultural commodity prices:

Price fluctuations are a common aspect of the agricultural sector. Factors such as weather, temperature changes, natural calamities, climate, and similar other factors, directly impact the prices of agricultural commodities.


Prices also fluctuate based on the farming zone in which the cultivation took place. Commodity price of the crop grown in the desert areas will be different when compared to the same crop grown in monsoon-heavy areas.


Price forecasting for agricultural commodities facilitates the stakeholders in the sector in a variety of ways:

● Helps farmers with sowing decisions:With price information of the crops in hand, farmers can decide whether they would like to sow a particular crop or not. It is also easy for them to back-calculate the profit margins associated with sowing a particular crop.


● Helps government make policy decisions:Price forecasting information also helps the government to decide on what the Minimum Selling Price (MSP) should be. MSP guarantees the farmers to sell their produce at a particular price, which insures them against any sharp fall in prices.

B. Sharing the current commodity prices.

Using big data applications, farmers can explore the current commodity prices in local markets. Because prices vary as per the local markets, districts, states, and nations, farmers can sell their produce as per the existing prices in markets. This gives them opportunities for better profit margins.


This also eliminates the need for intermediaries to sell. All the farmers must do is activate SMS/ Email alerts or install relevant big data applications that will give them instant price information in the nearest markets and directly sell there.


Big Data in Agriculture has certainly changed the way how the Agricultural sector operates. Big data applications have made operations and farming techniques efficient. It has also made crucial data accessible, which has further helped farmers make informed choices.


Thus, the application of big data analytics is a boon for Agriculture, and the stakeholders in the sector.